NVIDIA DGX Cloud is at the forefront of enterprise AI, providing the essential infrastructure and software for building, training, and deploying AI models at scale. As the demand for accelerated computing surges, robust capacity management becomes paramount. This role is crucial for ensuring dependable customer experiences and optimizing the utilization of our valuable GPU resources.

We are seeking a highly skilled Senior Software Engineer to architect and develop the sophisticated systems that seamlessly integrate customer demand with infrastructure supply, managing reservations, allocations, and utilization across all DGX Cloud environments. You will collaborate closely with diverse teams including engineering, product, operations, finance, and business to transform intricate capacity data and operational workflows into scalable software solutions and automated decision-making processes.

Design and implement distributed services and data pipelines critical for capacity planning, allocation, reservations, and utilization. Develop a comprehensive, unified model that reflects available, committed, and forecasted GPU capacity across various cloud providers, regions, clusters, and products. Automate complex capacity management workflows currently requiring manual analysis and coordination. Build essential APIs, tools, and integrations to empower other DGX Cloud systems and teams in making capacity-informed decisions. Enhance forecasting accuracy, scenario planning capabilities, and operational visibility by integrating demand signals with infrastructure supply data. Establish robust monitoring frameworks, data quality controls, and service-level indicators for all capacity systems. Lead technical design discussions, define engineering standards, and mentor fellow engineers. Diagnose and resolve complex production issues, focusing on improving the reliability, performance, and scalability of capacity management services.

A Bachelor of Science or equivalent experience in Computer Science, Computer Engineering, or a related technical discipline is required. Possess a minimum of 5 years of software engineering experience, with a proven track record of building and deploying production systems. Demonstrate strong programming proficiency in languages such as Python, Go, Java, or similar. Experience in designing and developing distributed systems, backend services, robust APIs, and efficient data-processing pipelines. Familiarity with cloud infrastructure, Kubernetes, compute platforms, or large-scale resource management systems is essential. A solid understanding of data modeling, system integration, observability principles, and production operations is expected. Ability to translate ambiguous business and operational requirements into clear, actionable technical designs. Excellent communication skills, with experience working effectively across both engineering and non-engineering organizational boundaries.